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The rapid advancement of Text-to-Image(T2I) generative models has enabled the synthesis of high-quality images guided by textual descriptions. Despite this significant progress, these models are often susceptible in generating contents that…

Computer Vision and Pattern Recognition · Computer Science 2024-06-25 Yichen Sun , Zhixuan Chu , Zhan Qin , Kui Ren

Current large-scale generative models have impressive efficiency in generating high-quality images based on text prompts. However, they lack the ability to precisely control the size and position of objects in the generated image. In this…

Computer Vision and Pattern Recognition · Computer Science 2023-04-27 Jiafeng Mao , Xueting Wang

Subject-consistent generation (SCG)-aiming to maintain a consistent subject identity across diverse scenes-remains a challenge for text-to-image (T2I) models. Existing training-free SCG methods often achieve consistency at the cost of…

Computer Vision and Pattern Recognition · Computer Science 2026-02-03 Zhanxin Gao , Beier Zhu , Liang Yao , Jian Yang , Ying Tai

For recent diffusion-based generative models, maintaining consistent content across a series of generated images, especially those containing subjects and complex details, presents a significant challenge. In this paper, we propose a new…

Computer Vision and Pattern Recognition · Computer Science 2024-05-03 Yupeng Zhou , Daquan Zhou , Ming-Ming Cheng , Jiashi Feng , Qibin Hou

Recent text-to-image (T2I) diffusion models have achieved remarkable progress in generating high-quality images given text-prompts as input. However, these models fail to convey appropriate spatial composition specified by a layout…

Computer Vision and Pattern Recognition · Computer Science 2023-11-28 Jiayu Xiao , Henglei Lv , Liang Li , Shuhui Wang , Qingming Huang

We focus on the foundational task of Scene Staging: given a reference scene image and a text condition specifying an actor category to be generated in the scene and its spatial relation to the scene, the goal is to synthesize an output…

Computer Vision and Pattern Recognition · Computer Science 2026-05-19 Cong Xie , Che Wang , Yan Zhang , Ruiqi Yu , Han Zou , Zheng Pan , Zhenpeng Zhan

In layout-to-image (L2I) synthesis, controlled complex scenes are generated from coarse information like bounding boxes. Such a task is exciting to many downstream applications because the input layouts offer strong guidance to the…

Computer Vision and Pattern Recognition · Computer Science 2025-03-18 Ruyu Wang , Xuefeng Hou , Sabrina Schmedding , Marco F. Huber

Despite significant advancements in text-to-image models for generating high-quality images, these methods still struggle to ensure the controllability of text prompts over images in the context of complex text prompts, especially when it…

Computer Vision and Pattern Recognition · Computer Science 2024-01-31 Zhenyu Wang , Enze Xie , Aoxue Li , Zhongdao Wang , Xihui Liu , Zhenguo Li

State-of-the-arts text-to-image generation models such as Imagen and Stable Diffusion Model have succeed remarkable progresses in synthesizing high-quality, feature-rich images with high resolution guided by human text prompts. Since…

Computer Vision and Pattern Recognition · Computer Science 2025-01-31 Ziyi Dong , Pengxu Wei , Liang Lin

Recent training-free layout-to-image diffusion models have demonstrated remarkable performance in generating high-quality images with controllable layouts. These models follow a one-stage framework: Encouraging the model to focus the…

Computer Vision and Pattern Recognition · Computer Science 2025-03-04 Linhao Huang , Jing Yu

Text-to-image synthesis has achieved high-quality results with recent advances in diffusion models. However, text input alone has high spatial ambiguity and limited user controllability. Most existing methods allow spatial control through…

Computer Vision and Pattern Recognition · Computer Science 2023-10-31 Yuki Endo

Recent text-to-image diffusion models are able to generate convincing results of unprecedented quality. However, it is nearly impossible to control the shapes of different regions/objects or their layout in a fine-grained fashion. Previous…

Computer Vision and Pattern Recognition · Computer Science 2023-09-06 Omri Avrahami , Thomas Hayes , Oran Gafni , Sonal Gupta , Yaniv Taigman , Devi Parikh , Dani Lischinski , Ohad Fried , Xi Yin

Text-to-image generation models can create high-quality images from input prompts. However, they struggle to support the consistent generation of identity-preserving requirements for storytelling. Existing approaches to this problem…

Computer Vision and Pattern Recognition · Computer Science 2025-02-06 Tao Liu , Kai Wang , Senmao Li , Joost van de Weijer , Fahad Shahbaz Khan , Shiqi Yang , Yaxing Wang , Jian Yang , Ming-Ming Cheng

Despite significant progress in Text-to-Image (T2I) generative models, even lengthy and complex text descriptions still struggle to convey detailed controls. In contrast, Layout-to-Image (L2I) generation, aiming to generate realistic and…

Computer Vision and Pattern Recognition · Computer Science 2024-03-14 Chengyou Jia , Minnan Luo , Zhuohang Dang , Guang Dai , Xiaojun Chang , Mengmeng Wang , Jingdong Wang

We propose a diffusion-based approach for Text-to-Image (T2I) generation with interactive 3D layout control. Layout control has been widely studied to alleviate the shortcomings of T2I diffusion models in understanding objects' placement…

Computer Vision and Pattern Recognition · Computer Science 2024-08-28 Abdelrahman Eldesokey , Peter Wonka

The task of layout-to-image generation involves synthesizing images based on the captions of objects and their spatial positions. Existing methods still struggle in complex layout generation, where common bad cases include object missing,…

Computer Vision and Pattern Recognition · Computer Science 2024-10-21 Bo Cheng , Yuhang Ma , Liebucha Wu , Shanyuan Liu , Ao Ma , Xiaoyu Wu , Dawei Leng , Yuhui Yin

Layout-to-Image generation aims to create complex scenes with precise control over the placement and arrangement of subjects. Existing works have demonstrated that pre-trained Text-to-Image diffusion models can achieve this goal without…

Computer Vision and Pattern Recognition · Computer Science 2025-06-19 Bonan Li , Yinhan Hu , Songhua Liu , Xinchao Wang

As cutting-edge Text-to-Image (T2I) generation models already excel at producing remarkable single images, an even more challenging task, i.e., multi-turn interactive image generation begins to attract the attention of related research…

Computer Vision and Pattern Recognition · Computer Science 2025-06-02 Junhao Cheng , Xi Lu , Hanhui Li , Khun Loun Zai , Baiqiao Yin , Yuhao Cheng , Yiqiang Yan , Xiaodan Liang

Diffusion-driven text-to-image (T2I) generation has achieved remarkable advancements in recent years. To further improve T2I models' capability in numerical and spatial reasoning, layout is employed as an intermedium to bridge large…

Computer Vision and Pattern Recognition · Computer Science 2026-03-10 Yuhao Jia , Wenhan Tan

Recent text-to-image generative models can generate high-fidelity images from text prompts. However, these models struggle to consistently generate the same objects in different contexts with the same appearance. Consistent object…

Computer Vision and Pattern Recognition · Computer Science 2023-10-12 Alec Helbling , Evan Montoya , Duen Horng Chau